NgsAdmixv2: Difference between revisions

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The method was published in 2013 and can be found here: [http://www.ncbi.nlm.nih.gov/pubmed/24026093]
The method was published in 2013 and can be found here: [http://www.ncbi.nlm.nih.gov/pubmed/24026093]
==Citation==
http://www.genetics.org/content/early/2013/09/03/genetics.113.154138.full.pdf
Skotte, L., Korneliussen, T. S., & Albrechtsen, A. (2013). Estimating individual admixture proportions from next generation sequencing data. Genetics, 195(3), 693–702. doi:10.1534/genetics.113.154138
:<u>'''Bibtex'''</u>
:% 24026093
:@Article{pmid24026093,
:  Author="Skotte, L.  and Korneliussen, T. S.  and Albrechtsen, A. ",
:  Title="{{E}stimating {I}ndividual {A}dmixture {P}roportions from {N}ext {G}eneration {S}equencing {D}ata}",
:  Journal="Genetics",
:  Year="2013",
:  Pages=" ",
:  Month="Sep"
:}


==Software Download==
==Software Download==
Line 116: Line 99:
==Input File==
==Input File==
Input files are contains genotype likelihoods in genotype likelihood beagle input file format [http://faculty.washington.edu/browning/beagle/beagle.html]. We recommend [[ANGSD]] for easy transformation of Next-generation sequencing data to beagle format. See [http://www.popgen.dk/angsd/index.php/Beagle_input Creation of Beagle files with ANGSD]
Input files are contains genotype likelihoods in genotype likelihood beagle input file format [http://faculty.washington.edu/browning/beagle/beagle.html]. We recommend [[ANGSD]] for easy transformation of Next-generation sequencing data to beagle format. See [http://www.popgen.dk/angsd/index.php/Beagle_input Creation of Beagle files with ANGSD]
Example of a beagle genotype likelihood input file for 3 individuals.
<pre>
marker      allele1  allele2  Ind0      Ind0    Ind0    Ind1    Ind1    Ind1    Ind2    Ind2    Ind2
1_14000023      1      0      0.941    0.058    0.000    0.799    0.199    0.001    0.666    0.333    0.001
1_14000072      2      3      0.709    0.177    0.112    0.941    0.058    0.000    0.665    0.332    0.001
1_14000113      0      2      0.855    0.106    0.037    0.333    0.333    0.333    0.799    0.199    0.000
1_14000202      2      0      0.835    0.104    0.060    0.799    0.199    0.000    0.333    0.333    0.333
...
</pre>
Column 1:The marker name (the information is not atually used)
Column 2 and 3: the major and minor allele (these two columns are not used within the program and can contain whatever dummy value).
The rest of the colums are the genotypes likelihoods (not in log space). For each individual we have 3 columns.
Note that the above values sum to one per sites for each individuals. This is just a normalization of the genotype likelihoods in order to avoid underflow problems in the beagle software it does not mean that they are genotype probabilities.


The input file is allowed to be compressed with gzip.
The input file is allowed to be compressed with gzip.
Line 148: Line 115:
* The .qopt file contains the admixture proportions for all individuals.
* The .qopt file contains the admixture proportions for all individuals.


Examples of the output files are found below.
==Citation==


http://www.genetics.org/content/early/2013/09/03/genetics.113.154138.full.pdf


===Log file (.log)===
Skotte, L., Korneliussen, T. S., & Albrechtsen, A. (2013). Estimating individual admixture proportions from next generation sequencing data. Genetics, 195(3), 693–702. doi:10.1534/genetics.113.154138
<div class="toccolours mw-collapsible mw-collapsed">
Contents of the file log file
<pre class="mw-collapsible-content">
-> Dumping file: tskSim/tsk6GL.beagle.s1.log
-> Dumping file: tskSim/tsk6GL.beagle.s1.filter
Input: lname=tskSim/tsk6GL.beagle nPop=3, fname=(null) qname=(null) outfiles=tskSim/tsk6GL.beagle.s1
Setup: seed=1 nThreads=10 method=1
Convergence: maxIter=2000 tol=0.000000 tolLike50=0.010000 dymBound=0
Filters: misTol=0.050000 minMaf=0.000000 minLrt=0.000000 minInd=0
Input file has dim: nsites=100000 nind=75
Input file has dim (AFTER filtering): nsites=100000 nind=75
iter[start] like is=9299805.984931
iter[50] like is=-6531138.892608 thres=0.002800
iter[100] like is=-6528710.773349 thres=0.001289
iter[150] like is=-6528405.896951 thres=0.001211
iter[200] like is=-6528306.803820 thres=0.000420
iter[250] like is=-6528277.160993 thres=0.000546
iter[300] like is=-6528271.925055 thres=0.000033
iter[350] like is=-6528271.177692 thres=0.000008
iter[400] like is=-6528270.876315 thres=0.000005
iter[450] like is=-6528270.772894 thres=0.000140
iter[500] like is=-6528270.747721 thres=0.000002
iter[550] like is=-6528270.740654 thres=0.000002
Convergence achived because log likelihooditer difference for 50 iteraction is less than 0.010000
best like=-6528270.740654 after 550 iterations
-> Dumping file: tskSim/tsk6GL.beagle.s1.qopt
-> Dumping file: tskSim/tsk6GL.beagle.s1.fopt.gz
[ALL done] cpu-time used =  671.82 sec
[ALL done] walltime used =  114.00 sec
</pre>
</div>


===Allele frequency ouput (.fopt)===
:<u>'''Bibtex'''</u>
Each column correponds to the estimated allele frequencies for each population and each line is a SNP
:% 24026093
<div class="toccolours mw-collapsible mw-collapsed">
:@Article{pmid24026093,
Example of a .fopt file for -K 3
:  Author="Skotte, L. and Korneliussen, T. S. and Albrechtsen, A. ",
<pre class="mw-collapsible-content">
:  Title="{{E}stimating {I}ndividual {A}dmixture {P}roportions from {N}ext {G}eneration {S}equencing {D}ata}",
...
:  Journal="Genetics",
0.75331646167520038837 0.51190946588401886608 0.50134051056701267601
:  Year="2013",
0.99999999900000002828 0.80165850924934911603 0.97470665326916294813
:  Pages=" ",
0.99999999900000002828 0.89560828888972687789 0.88062641752218895341
:  Month="Sep"
0.99999999900000002828 0.99999999900000002828 0.86109994249930577048
:}
0.70560445653074521655 0.78994686954000448154 0.93076614062025020413
0.99999999900000002828 0.88878537780630872955 0.92662857068149151463
0.05322676762098016434 0.22871739860812340117 0.17394852600322696645
0.00000000100000000000 0.27428885137150410545 0.19029599645013275944
0.57086006389212373691 0.42232596591112880891 0.74080063581586474974
0.77359733910003525281 0.47380864146016693494 0.72073560889718923939
0.49946404159405927148 0.21684946347150244050 0.15201985942558055021
0.41802171086717271331 0.55490556205954566504 0.85691127728452165524
0.77095213528720529794 0.60074618451005279418 0.70219544996184157792
0.26517850405564091787 0.48500265408436060710 0.85432254709914456914
0.80055081986260245852 0.74423201242010783574 0.87110476762969968334
0.30563054476851375663 0.05233529475348827620 0.25911912824038613179
0.51084997710733415222 0.62263692178557350498 0.50738250264097506381
0.64790272562679740442 0.91230541484222271720 0.73015721390331478347
0.07124629651164265942 0.37896482494356753534 0.29218012479334326548
0.00000000100000000000 0.26969100790961914038 0.28395781874856029781
0.97074775756045073027 0.79093498372643300520 0.64006920058897498471
0.64661948716978157048 0.84130009558421925409 0.76730057769159087933
0.86990900887920663553 0.79410745692063922085 0.69416721874359499367
0.34956069940263900797 0.27773038429396151860 0.25923476721423144298
0.77739744690560164120 0.51272232330145017798 0.53888718200036844763
0.35431569298041332150 0.20022780744715171219 0.43176580786072032980
0.91858160919413811563 0.99999999900000002828 0.93584179237779097082
0.90339823126358831384 0.94729687041528465308 0.84358671720630329371
0.87068129661127857677 0.65267891763324525911 0.59315740612546075106
0.24102496839012735319 0.42777100607917967201 0.39594098602469629533
0.99999999900000002828 0.99999999900000002828 0.78549330115836857313
0.15386277372522660922 0.18035502891341426146 0.26583557049163752950
0.22456748943597096280 0.25110807159057474403 0.17244618960511531869
0.74816053649164548922 0.54769319158907958656 0.44532166240679449398
0.76350303696805599252 0.86547244122202959815 0.94111974586621383043
0.40940400475566068872 0.67767095908245833513 0.40793761498610620064
0.85389765162910868934 0.78901563183853873351 0.93614065916219291186
0.54108661985898742763 0.61895909938546000983 0.88522763262549941654
0.99051495581855464323 0.78855843624128341141 0.77646441702623147929
0.51133721761171413434 0.74521610846562824637 0.32689774480116673416
0.66618479413060949224 0.67891474309775079465 0.80762116232856140385
0.81793598261160704865 0.77752326447671193943 0.95349025244041396565
0.82120324647844433752 0.99999999900000002828 0.89800731971059466474
...
</pre>
</div>
Use the "-printInfo 1" option to get the position of the lines in the fopt file if some sites have been flltered from the analysis (-minMaf, minInd, minLRT etc)
 
===Admixture proportion output file (.qopt)===
Infered admixture proporsions. Each line is an individual and each column is a population.
<div class="toccolours mw-collapsible mw-collapsed">
Contents of the qopt file # cat tsk48GL.beagle.gz.s1.qopt
<pre class="mw-collapsible-content">
0.00254460532103031574 0.00108987228478324210 0.99636552239418640919
0.00000015905647541105 0.00000000100000000000 0.99999983994352459327
0.00034770382567266174 0.02639209238328452459 0.97326020379104283275
0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
0.00000467398081877176 0.00000000100000000000 0.99999532501918120264
0.00000000907496942853 0.00585150933779484805 0.99414848158723567728
0.00515826525767644137 0.01138897436535154552 0.98345276037697204607
0.03914841746468285949 0.00000000100000000000 0.96085158153531713410
0.00000000100000000000 0.00629199375758324100 0.99370800524241675866
0.00771173022930659625 0.00000154720357311662 0.99228672256712036059
0.00000000100000000000 0.00075135345721917719 0.99924864554278081119
0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
0.00000005468413042120 0.00087279924180633879 0.99912714607406327705
0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
0.00712941313019542066 0.00118955677574110528 0.99168103009406338710
0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
0.00000000100000000000 0.00165385222968000606 0.99834614677032007535
0.00000000100000000000 0.00006297763597355473 0.99993702136402651259
0.00519087111391381209 0.00000000100000000000 0.99480912788608621966
0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
0.00202872783596746379 0.00000000100000000000 0.99797127116403261393
0.00876424336999809782 0.00949457841911990376 0.98174117821088191516
0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
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0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
0.01820430093358888640 0.00000694033297829119 0.98178875873343274261
0.00351013812443964728 0.00000020340562512923 0.99648965846993520223
0.00771897550085272680 0.00605259705033356268 0.98622842744881378252
0.00600595292580561029 0.00000000100000000000 0.99399404607419439284
0.01454910070242997067 0.00543457657939076105 0.98001632271817917808
0.02567862615486414535 0.00160921436783232220 0.97271215947730349516
0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
0.00000000100000000000 0.00001041560507852223 0.99998958339492149960
0.00000000100000000000 0.01383432553657116572 0.98616567346342876021
0.00343840097404925389 0.00000000100000000000 0.99656159802595079000
0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
0.00051244065751142103 0.00404846039501185508 0.99543909894747661937
0.02003953974792894652 0.00000004934009128878 0.97996041091197982897
0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
0.02176809890633762956 0.00000000100000000000 0.97823190009366245423
0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
0.01563096189267457192 0.00970868396771427770 0.97466035413961116252
0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
0.00002540964943070735 0.00000000100000000000 0.99997458935056915408
0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
0.99501476026684787524 0.00000000100000000000 0.00498523873315206718
0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
0.99520671498720802983 0.00479241730266987201 0.00000086771012207898
0.95884374919730619435 0.00000000100000000000 0.04115624980269377842
0.99002104218586972628 0.00000000100000000000 0.00997895681413022567
0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
0.99999999770925251941 0.00000000129074746013 0.00000000100000000000
0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
0.98980053177767901573 0.00000005577971952226 0.01019941244260143612
0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
0.99999785004878083416 0.00000000100000000000 0.00000214895121910354
0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
0.99220030909132039820 0.00000000100000000000 0.00779968990867968733
0.99999996788621803301 0.00000000100000000000 0.00000003111378189772
0.99736783433174225344 0.00255940950853666971 0.00007275615972113173
0.99998096423035520708 0.00000000574461213317 0.00001903002503262207
0.99711097909957713270 0.00288887008493822353 0.00000015081548462101
0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
0.99769262012085335734 0.00000000100000000000 0.00230737887914652393
0.99999820787375570674 0.00000000433914936351 0.00000178778709493472
0.98047422489554170166 0.00012980111977614777 0.01939597398468214523
0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
0.98208006049140339488 0.00000000100000000000 0.01791993850859651197
0.97530298545159921364 0.00000000100000000000 0.02469701354840085974
0.99657542812406740840 0.00000000100000000000 0.00342457087593254226
0.99954556420189066834 0.00045443479810919004 0.00000000100000000000
0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
0.99531584565237773976 0.00410740812985130408 0.00057674621777084644
0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
0.99878572597704817770 0.00000000100000000000 0.00121427302295177490
0.98571687209123504125 0.00400077401169816448 0.01028235389706666329
0.99027397554762419674 0.00840892511494516215 0.00131709933743062008
0.99999993504923445631 0.00000000100000000000 0.00000006395076564386
0.95946639819101930957 0.00000000100000000000 0.04053360080898076034
0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
0.98414939425022363029 0.01585059024074651421 0.00000001550902978739
0.99999999622245250297 0.00000000277754757396 0.00000000100000000000
0.99525652466242930938 0.00000001683386219288 0.00474345850370842034
0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
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0.99999965447943561792 0.00000000100000000000 0.00000034452056438734
0.99864814059528783652 0.00135185840471215468 0.00000000100000000000
0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
0.00000000100000000000 0.99999999800000005656 0.00000000100000000000
0.00000001076370464123 0.99999998823629543399 0.00000000100000000000
0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
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0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
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0.00000000100000000000 0.99999999800000005656 0.00000000100000000000
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0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
0.00000000100000000000 0.99999999800000005656 0.00000000100000000000
0.00000000100000000000 0.99999986659623718577 0.00000013240376283687
0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
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0.00000000100000000000 0.99632783404679736705 0.00367216495320256799
0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
0.00000000099999999999 0.99999999800000005656 0.00000000099999999999
0.35919621347731411909 0.32381633362411937904 0.31698745289856661289
0.31048363757756514136 0.30902410742704566893 0.38049225499538924522
0.36341140678787386964 0.33678307361394943520 0.29980551959817652863
0.34550713774447228133 0.34037087985425079628 0.31412198240127681137
0.34705579219215104692 0.35218792485566730033 0.30075628295218165276
0.33646039412306782967 0.32632754139618752598 0.33721206448074481088
0.31881401220765009930 0.34885621407165418040 0.33232977372069577582
0.34999374672052624424 0.33030931848049555066 0.31969693479897826061
0.33152251818028721786 0.32339147992992234304 0.34508600188979043910
0.31959998197389311025 0.33152491237148390413 0.34887510565462298562
0.34724548642936803322 0.31809475756470984020 0.33465975600592196004
0.33378069767858009609 0.33223636639277298599 0.33398293592864686241
0.32023090400419051971 0.33179989332826043125 0.34796920266754916007
0.35205158009776410521 0.33547091017851976558 0.31247750972371612921
0.34291063455495451873 0.31853488093100223999 0.33855448451404313026
0.31929132670383747472 0.32755905579808902717 0.35314961749807355362
0.34114474726121107873 0.34607065583774476725 0.31278459690104404300
0.33725705347681012025 0.32910919226619778089 0.33363375425699209886
0.33918213722968154622 0.32278745806952213737 0.33803040470079642743
0.33788659799509024317 0.34692305448657090317 0.31519034751833896468
0.35876135180876589370 0.33843260979944000955 0.30280603839179404124
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</pre>
</div>

Revision as of 11:27, 25 June 2019

This page contains information about the program called NGSadmix, which is a very nice tool for estimating individual admixture proportions from NGS data. It is based on genotype likelihoods and works well for medium and low coverage NGS data. It is a fancy multithreaded c/c++ program which makes it useful for large datasets.

The great thing about NGSadmix is that it is a new method that takes the uncertainty introduced in NGS sequencing data into account when inferring an individual's ancestry by using genotype likelihoods that considers the uncertainty caused by unobserved genotypes.

REMEMBER TO EDIT AND CITE: "NGSadmix is only sensitive to admixture recent enough to cause structures in the population in terms of differing allele frequencies. Historical admixture events after which many generations has passed in the population, leaves no signature in terms of systematic differences in allele frequencies between individuals and are not a concern in association studies. " ADD ADMIXTURE AND STRUCTURE AS

The method was published in 2013 and can be found here: [1]

Software Download

The latest version of NGSadmix is ngsadmix32 from June 25, 2013 and can be downloaded here: [2].

Older Versions
The previous version of NGSadmix, ngsadmix31 can be found here: [3].
Version Log:
  • v32 june 25-2013; modified code such that it now compiles on OSX
  • v31 june 24-2013; First public version.

Installation

NGSadmix can be installed independently or as a part of ANGSD.

NGSadmix Independent Installation

1. Login to your server using ssh on your terminal window.

2. Create the directory where you will install your software and enter it, such as

mkdir ~/Software
cd ~/Software

3. Download the source code:

wget https://raw.githubusercontent.com/ANGSD/angsd/master/misc/ngsadmix32.cpp

4. Configure, Compile and Install:

g++ ngsadmix32.cpp -O3 -lpthread -lz -o NGSadmix

5. Delete source code to save space:

rm ~/Software/ngsadmix32.cpp

NGSadmix Installation from ANGSD



Run command example

Download the input file

wget popgen.dk/software/download/NGSadmix/data/input.gz

Execute NGSadmix

./NGSadmix -likes input.gz -K 3 -P 4 -o myoutfiles -minMaf 0.05

Detailed Examples and Tutorial

Please refer to the tutorial's page [4]

Parameters

./NGSadmix


*** see doc for options/possible ranges/ and further explanation

Arguments:
	-likes .beagle format filename with genotype likelihoods
	-K Number of ancestral populations
Optional:
	-fname Ancestral population frequencies
	-qname Admixture proportions
	-outfiles Prefix for output files
	-printInfo print ID and mean maf for the SNPs that were analysed
Setup:
	-seed Seed for initial guess in EM
	-P Number of threads
	-method If 0 no acceleration of EM algorithm
	-misTol Tolerance for considering site as missing
Stop criteria:
	-tolLike50 Loglikelihood difference in 50 iterations
	-tol Tolerance for convergence
	-dymBound Use dymamic boundaries (1: yes (default) 0: no)
	-maxiter Maximum number of EM iterations
Filtering
	-minMaf Minimum minor allele frequency
	-minLrt Minimum likelihood ratio value for maf>0
	-minInd Minumum number of informative individuals

NB All parameters are set using '''-par value'''. So to get additional information you would write '''-printInfo 1'''.

Input File

Input files are contains genotype likelihoods in genotype likelihood beagle input file format [5]. We recommend ANGSD for easy transformation of Next-generation sequencing data to beagle format. See Creation of Beagle files with ANGSD

The input file is allowed to be compressed with gzip.

Output Files

Program outputs 3 files.

  1. PREFIX.log
  2. PREFIX.fopt.gz
  3. PREFIX.qopt
  • The .log file contains log information of the run. Commandline used for running the program, what the likelihood is every 50 iterations, and finally how long it took to do the run.
  • The .fopt.gz file is an compressed file, which contains an estimate of the frequency for each site for all populations.
  • The .qopt file contains the admixture proportions for all individuals.

Citation

http://www.genetics.org/content/early/2013/09/03/genetics.113.154138.full.pdf

Skotte, L., Korneliussen, T. S., & Albrechtsen, A. (2013). Estimating individual admixture proportions from next generation sequencing data. Genetics, 195(3), 693–702. doi:10.1534/genetics.113.154138

Bibtex
% 24026093
@Article{pmid24026093,
Author="Skotte, L. and Korneliussen, T. S. and Albrechtsen, A. ",
Title="{{E}stimating {I}ndividual {A}dmixture {P}roportions from {N}ext {G}eneration {S}equencing {D}ata}",
Journal="Genetics",
Year="2013",
Pages=" ",
Month="Sep"
}